configs/pretrain/fiber_cc.yaml

MODEL:
  META_ARCHITECTURE: "GeneralizedVLRCNN"
  WEIGHT: "MODEL/swin_base_patch4_window7_224.pth"
  RPN_ONLY: True
  RPN_ARCHITECTURE: "VLDYHEAD"

  BACKBONE:
    FUSION_VERSION: "v2"
    CONV_BODY: "SWINT-FPN-RETINANET"
    OUT_CHANNELS: 256

  SWINT:
      VERSION: "fusion"
      EMBED_DIM: 128
      DEPTHS: (2, 2, 18, 2)
      NUM_HEADS: (4, 8, 16, 32)
      WINDOW_SIZE: 12
      OUT_CHANNELS: (128, 256, 512, 1024)
      DROP_PATH_RATE: 0.4

  LANGUAGE_BACKBONE:
    FREEZE: False
    MODEL_TYPE: "roberta-fused-v2"
    MASK_SPECIAL: False
    TOKENIZER_TYPE: "roberta-base"
    USE_CHECKPOINT: False

  RPN:
    USE_FPN: True
    ANCHOR_SIZES: (64, 128, 256, 512, 1024)
    ANCHOR_STRIDE: (8, 16, 32, 64, 128)
    ASPECT_RATIOS: (1.0,)
    SCALES_PER_OCTAVE: 1

  DYHEAD:
    CHANNELS: 256
    NUM_CONVS: 6
    USE_GN: True
    USE_DYRELU: True
    USE_DFCONV: True
    USE_DYFUSE: True
    TOPK: 9 # topk for selecting candidate positive samples from each level
    SCORE_AGG: "MEAN"
    LOG_SCALE: 0.0

    USE_CHECKPOINT: True
    FUSE_CONFIG:
      USE_FUSED_FEATURES_DOT_PRODUCT: False
      EARLY_FUSE_ON: False
      TYPE: "NONE"   # "MHA-B", "MHA-S", "FILM", "SCAN", "NONE"
      USE_CLASSIFICATION_LOSS: False
      USE_TOKEN_LOSS: False
      USE_CONTRASTIVE_ALIGN_LOSS: False
      CONTRASTIVE_HIDDEN_DIM: 64
      USE_DOT_PRODUCT_TOKEN_LOSS: True
      USE_LAYER_SCALE: True
      CLAMP_MIN_FOR_UNDERFLOW: True
      CLAMP_MAX_FOR_OVERFLOW: True
      CLAMP_BERTATTN_MIN_FOR_UNDERFLOW: True
      CLAMP_BERTATTN_MAX_FOR_OVERFLOW: True
      CLAMP_DOT_PRODUCT: True

DATASETS:
  REGISTER:
    bing_caption_train:
      yaml_path: "GCC/CC3M/yamls"
      yaml_name: "tiny.noun.harsh"
      yaml_name_no_coco: "tiny.noun.harsh"

  # PREDOWNLOAD_BING : True
  # PREDOWNLOAD_WITH_AZCOPY : True

  CAPTION_CONF: 0.4
  CAPTION_AUGMENTATION_VERSION: "v3.v1"
  CAPTION_VOCAB_FILE: "tools/files/mixed_vocab.v1.tmp0.davincci.chunk1of1.filtered.json"
  DESCRIPTION_FILE: "tools/files/o365.description.v1.json"

  TRAIN:  ("mixed_train_no_coco", "flickr30k_train", "object365_dt_train", "bing_caption_train_no_coco")
  #  TRAIN: ("bing_caption_train", "mixed_train", "flickr30k_train", "coco_grounding_train", )
  TEST: ("coco_2017_val", )
  BING_INDEX_LIST: [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
  # BING_INDEX_LIST: [ 0, 1, ]
  ONE_HOT: False
  FLICKR_COPY: 2
  MIXED_COPY: 2
  OBJECT365_COPY: 2
  DISABLE_SHUFFLE: False
  ADD_DET_PROMPT: False
  RANDOM_SAMPLE_NEG: 85
  CONTROL_PROB: (0.05, 0.05, 0.5, 0.2)
  FURTHER_SCREEN: True
  
  CAPTION_NMS: -1.0
  CAPTION_MIN_BOX: 1

  SEPARATION_TOKENS: ". "

  PACK_RANDOM_CAPTION_NUMBER: 20
  NO_RANDOM_PACK_PROBABILITY: 0.4
  RANDOM_PACK_PROB: 0.5
  CAPTION_FORMAT_VERSION: "v2"

INPUT:
  PIXEL_MEAN: [ 103.530, 116.280, 123.675 ]
  PIXEL_STD: [ 57.375, 57.120, 58.395 ]
  MIN_SIZE_TRAIN: 800
  MAX_SIZE_TRAIN: 1333
  MIN_SIZE_TEST: 800
  MAX_SIZE_TEST: 1333

AUGMENT:
  MULT_MIN_SIZE_TRAIN: (480,560,640,720,800)

DATALOADER:
  SIZE_DIVISIBILITY: 32
  DISTRIBUTE_CHUNK_AMONG_NODE: False

SOLVER:
  OPTIMIZER: ADAMW
  BASE_LR: 0.0001
  LANG_LR: 0.00001
  WEIGHT_DECAY: 0.01
  WEIGHT_DECAY_SCHEDULE: True
  STEPS: (0.67, 0.89)
  MAX_ITER: 235026
  IMS_PER_BATCH: 64
  WARMUP_ITERS: 2000
  WARMUP_FACTOR: 0.001
  TEST_WITH_INFERENCE: True
  FIND_UNUSED_PARAMETERS: False
  USE_AMP: True
  MODEL_EMA: 0.999
  CHECKPOINT_PERIOD: 2500


  CLIP_GRADIENTS:
    ENABLED: True
    CLIP_TYPE: "full_model"
    CLIP_VALUE: 1.0
    NORM_TYPE: 2.0

TEST:
  DURING_TRAINING: False
  IMS_PER_BATCH: 64